Data Engineer Jobs in Saxony-Anhalt, Germany

Data Engineering team at Ultra Tendency builds scalable data platforms for international clients. The Senior Data Engineer designs, implements and maintains Databricks Lakehouse pipelines, optimizes batch and streaming workflows, collaborates with cross‑functional teams, and mentors junior engineers.

Data Engineer at Carl Zeiss Meditec AG responsible for developing and evolving the Microsoft Azure big data platform, building cloud solutions to extract and analyze data from medical devices, developing algorithms and software tools for unstructured device data, collaborating with cross‑functional teams, and delivering insights through visualizations. Requires university degree, 3+ years experience, strong Python, SQL, Bash, Azure/AWS, ETL, Power BI, Spark, Databricks, and communication in English and German.

European Delivery organisation at Cognite - AI for Industry builds industrial AI and data solutions. As Data Engineering Leader you will lead and develop a team of Data Engineers, delivering complex AI engagements while maintaining ~50% billable capacity on customer projects.

Data Engineering team responsible for rebuilding trust in a regulated credit and lending data environment. The Data Engineer will transform a centralized data lake into an analytics-ready foundation, designing and enforcing data quality, lineage, and governance across AWS and Spark pipelines.

Product Data Engineering team builds the data and machine learning foundation that powers user engagement, personalization, and product growth. The Data Engineer designs, builds and maintains scalable ETL/ELT pipelines, develops data transformation workflows for feature engineering, collaborates with ML engineers to deliver reliable inputs for recommendation and predictive models, and ensures data quality and performance across batch and near‑real‑time workloads.

Data Engineer on the forward‑thinking engineering team building the data foundation for next‑generation AI and cloud technologies. Designs, develops and maintains scalable data pipelines and infrastructure that power analytics, reporting and strategic decision‑making across a global platform.

Data Engineering & Prozessoptimierung Team at Robert Bosch GmbH focuses on building and operating ETL jobs, designing business logic in databases, and visualizing data in dashboards. The intern will independently support the team in preparing the transition from SAP R/3 to S/4 HANA, analyze business processes with Celonis, and co‑design standardization measures.

Tipico’s Data Engineering team builds high‑velocity pipelines that power AI and analytics for sports betting. The role designs and maintains batch and real‑time ELT workflows using AWS, Snowflake, DBT, Airflow, and Spark to deliver actionable insights on customer acquisition and operational efficiency.

Customer Experience team at T‑Systems Iberia builds data pipelines to keep Germany’s mobile network at peak performance. The role designs and runs GCP‑based ETL workflows, validates data, and delivers actionable insights to mobile service experts.

Data Engineering, Data Science and Data Analysis team at Sopra Steria building innovative solutions on the Palantir Foundry platform. The role designs, develops, and maintains data pipelines, transformations, and analytical dashboards while driving best practices in big‑data technologies.

Data Engineering Team at Statista builds and maintains the tracking data infrastructure that captures millions of user events daily. The role owns ELT pipelines, ensures data quality, and drives cost efficiency across AWS, Snowflake, and orchestration tools.

Deel’s Data Engineering team builds the backbone of our global payroll and HR platform, turning raw data from 150+ countries into actionable insights. The role designs, builds, and maintains efficient ETL pipelines, optimizes data warehouse schemas, and writes complex SQL and Python scripts to support analytics and reporting.

At Kpler, a global data intelligence firm, the Data Engineer will enhance pipelines that retrieve, normalize, and distribute large commodity datasets for the European power market. Responsibilities include expanding data coverage to new markets, enriching product features, building monitoring dashboards, and optimizing API performance.

Data Engineer at Kpler focused on dry bulk commodities. Build tools, CLI utilities, and Streamlit UIs to enable analysts to perform data quality interventions at scale.

Statista, a global business data platform, seeks a Junior Data Engineer to build and maintain scalable data pipelines, orchestrate workflows with Airflow, and optimize data infrastructure. The role involves collaborating with data sourcing and architecture teams, developing ETL processes in Python, and ensuring high availability and security of data services.

Nebius seeks a Data Engineer to build and maintain scalable data pipelines that power analytics and business intelligence across its AI cloud platform. The role involves designing data infrastructure, optimizing storage and processing, implementing quality monitoring, and ensuring governance and compliance.

Statista seeks a Data Engineering Lead to guide a team of Data & AI engineers in building scalable, cloud-native solutions. The role blends leadership with hands‑on engineering, driving end‑to‑end development of AI‑powered data pipelines, automation frameworks, and agentic workflows.

Data Platform department at Sartorius Corporate Administration GmbH builds scalable data pipelines on Azure to empower business decisions. The role designs, develops, and maintains Azure Data Factory, Databricks, and Data Lake workflows, ensuring data quality and governance while collaborating with analysts, scientists, and stakeholders.

Data Engineering team at Staffbase builds a self‑service data platform that powers AI‑enabled product features. The Staff Engineer drives technical direction, leads architecture decisions, mentors a team of engineers, and owns the data lake, semantic layer and governance.

Data Engineering – ML Infrastructure team at Qonto builds the data layer powering the company’s AI products. The role designs and maintains Python pipelines, feature stores, and model serving infrastructure that enable ML engineers to focus on models rather than plumbing.